Caris Moses, PhD

carism at mit dot edu



I recently graduated from MIT where I worked in the Learning and Intelligent Systems Group within the Computer Science and Artificial Intelligence Lab (CSAIL) with Professors Tomás Lozano-Pérez and Leslie Pack Kaelbling. I work at the intersection of robotics and artificial intelligence, and am interested in developing robots that have the ability to reason about low-level physics while trying to accomplish long-horizon manipulation tasks. In my work I explore ways of leveraging active learning to aid in efficient data collection for learning accurate action models.

I am also very passionate about issues of diversity, equity, and inclusion in the spaces I occupy. You can see some of my recommended resources here.


Massachusetts Institute of Technology
PhD in Electrical Engineering and Computer Science, May 2022
Minor: African American Studies
Advisors: Leslie Pack Kaelbling, Tomás Lozano-Pérez
[thesis] Optimistic Active Learning of Task and Action Models for Robotic Manipulation

Northestern University
MS in Computer Science, December 2015
Advisors: Robert Platt and Rahul Chipalkatty (Draper)
[thesis] Multi-Agent UAV Planning Using Belief Space Hierarchical Planning in the Now

Cornell University
BS in Mechanical Engineering, September 2013


  • Wevolver Innovators Update: Teaching robots to get curious
    [article and video]
  • MIT Technology Review's EmTech Digital Conference
    Active Learning of Abstract Plan Feasibility [video]


  • Caris Moses, Leslie Pack Kaelbling, Tomás Lozano-Pérez. Learning to Plan with Optimistic Action Models. ICRA Worksop - Scaling Robot Learning, 2022. [paper]
  • Michael Noseworthy*, Caris Moses*, Isaiah Brand*, Sebastian Castro, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy. Active Learning of Abstract Plan Feasibility. Robotics: Science and Systems (RSS), 2021. [paper] [video]
  • Michael Noseworthy*, Caris Moses*, Isaiah Brand*, Sebastian Castro, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy. Curiosity-Driven Learning of Abstract Plan Feasibility. ICRA Worksop - Towards Curious Robots: Modern Approaches for Intrinsically-Motivated Intelligent Behavior, 2021. [paper]
  • Caris Moses, Jane Shi. Integrating State Estimation and Perception for Picking. IROS Worksop on Why Robots Fail to Grasp, 2020. [paper]
  • Caris Moses*, Michael Noseworthy*, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy. Visual Prediction of Priors for Articulated Object Interaction. IEEE International Conference on Robotics and Automation (ICRA), 2020. [website]
  • Caris Moses, Rahul Chipalkatty, Rob Platt. Belief Space Hierarchical Planning in the Now for Unmanned Aerial Vehicles. AIAA Infotech@Aerospace, 2016. [paper]
  • Rashi Tiwari*, Michael A Meller*, Karl B Wajcs, Caris Moses, Ismael Reveles, Ephrahim Garcia. Hydraulic artificial muscles. Journal of Intelligent Material Systems and Structures, 23(3), 301-312, 2012. [paper]


  • Amazon Robotics (2020)
    Integrated state estimation with segmentation to predict errors in the segmentation. See workshop paper for more details.
  • Mujin (2017)
    Worked on verification methods for a bin-picking robotic system in order to prevent failures before they were encountered on the deployed robots.

Selected Projects

  • Peg Insertion with Policy Search
    Dynamic Programming and Stochastic Control, 6.231, Spring 2017, MIT
    [report] [slides]
  • Template Matching in Image Colorization
    Advances in Computer Vision, 6.869, Fall 2017, MIT
  • Localization and Reference Tracking in Mobile Robots
    UCSD STARS, Summer 2012, UC San Diego
    [real robot video] [rviz view video] [slides]
  • The 99% Robot - My very first robot!
    Mechatronics, MAE 3780, Spring 2012, Cornell University
    [video1] [video2] [report] [slides]


  • Robotics: Science and Systems (6.141/16.405) - Teaching Assistant (Spring 2020)

Selected Awards